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» Finding Frequent Patterns in a Large Sparse Graph
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IDA
2009
Springer
14 years 7 months ago
Mining the Temporal Dimension of the Information Propagation
In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possibl...
Michele Berlingerio, Michele Coscia, Fosca Giannot...
ICDM
2010
IEEE
208views Data Mining» more  ICDM 2010»
14 years 7 months ago
Bonsai: Growing Interesting Small Trees
Graphs are increasingly used to model a variety of loosely structured data such as biological or social networks and entityrelationships. Given this profusion of large-scale graph ...
Stephan Seufert, Srikanta J. Bedathur, Juliá...
GROUP
2005
ACM
15 years 3 months ago
Proactive support for the organization of shared workspaces using activity patterns and content analysis
Shared workspace systems provide virtual places for selforganized and semi-structured cooperation between local and distributed team members. These cooperation systems have been a...
Wolfgang Prinz, Baber Zaman
SDM
2010
SIAM
283views Data Mining» more  SDM 2010»
14 years 11 months ago
Cascading Spatio-temporal Pattern Discovery: A Summary of Results
Given a collection of Boolean spatio-temporal(ST) event types, the cascading spatio-temporal pattern (CSTP) discovery process finds partially ordered subsets of event-types whose ...
Pradeep Mohan, Shashi Shekhar, James A. Shine, Jam...
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
15 years 4 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...